July 14, 2022, 1:20 a.m. | Yong Xie, Dakuo Wang, Pin-Yu Chen, Jinjun Xiong, Sijia Liu, Sanmi Koyejo

cs.CR updates on arXiv.org arxiv.org

More and more investors and machine learning models rely on social media
(e.g., Twitter and Reddit) to gather real-time information and sentiment to
predict stock price movements. Although text-based models are known to be
vulnerable to adversarial attacks, whether stock prediction models have similar
vulnerability is underexplored. In this paper, we experiment with a variety of
adversarial attack configurations to fool three stock prediction victim models.
We address the task of adversarial generation by solving combinatorial
optimization problems with semantics …

adversarial attack predictions stock word

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